ISSN 1330-3651 (Print), ISSN 1848-6339 (Online) https://doi.org/10.17559/TV-20170809140304 Original scientific paper

Analysis of Climate Change Impact on Water Supply in Northern ()

Barbara KARLEUŠA, Josip RUBINIĆ, Maja RADIŠIĆ, Nino KRVAVICA

Abstract: This paper analyses impacts of climate change and anthropogenic pressure on groundwater resources in the Mirna river catchment used for water supply in Northern Istria (Croatia) up to 2050. Using Regional Climate Models simulations and hydrologic model, the future average annual and the characteristic (in critical period) water resource availabilities were calculated. Current and five future water demand scenarios were analysed. Water Exploitation Index (WEI) and modified Characteristic Water Exploitation Index (CWEI) were calculated. In 2050, the analysed springs will be subject to climate change consequences, with more extreme changes and intense variations. The WEI for average conditions indicates little risk of unmet future water demand. Considering seasonal variability, the future CWEIs indicates strong risk for most future water demand scenarios and overexploitation for water demand increases over 20%. The 2012 drought, more extreme than any considered future scenario, was also examined.

Keywords: climate change; drinking water supply; water resources availability

1 INTRODUCTION Regardless of the methodology used to simulate climate change, the impact of climate change on the water The Mediterranean basin, including the resources in the Mediterranean has been confirmed in region, is a region that is very sensitive to climate change different studies [13-15]. Based on scenarios of varying and anthropogenic impacts [1]. According to Xoplaki et al. future temperature and precipitation to analyse the changes [2], since the 1970s, the mean annual temperatures in the in groundwater recharge and in agricultural water demand Mediterranean region have increased by 0.1 °C per decade, for the West Bank of the Mediterranean basin, Mizyed 15] and precipitation has decreased by 25 mm per decade. concluded that the groundwater recharge could decrease by Temperatures are expected to increase by 1.5-2.5°C, and up to 50%. precipitation is expected to decrease by 5% to 20% up to Water supply system and sources vulnerability due to 2050 [3], which could significantly decrease (30-50%) climate change are analysed by researchers in the freshwater resources throughout the Mediterranean basin. Monterrey Metropolitan Area of northern Mexico [7] and In the Adriatic region, the decrease of 15% of freshwater is on Mexico City [16]. However, only a small number of expected in northern Italy and the Balkans [3]. Climate papers have investigated mitigation measures and adaptive changes cause more frequent drought and flood strategies for drinking water supply [4, 17]. occurrence. On the other hand, an increase in water Impact of climate change on water resources used for demand is expected due to increasing urbanisation, drinking water supply in the Adriatic region has been agricultural production and tourism activities, increasing investigated within the DRINKADRIA project [18, 19]. the withdrawal of and pressures on regional water This paper presents the investigation of the climate resources [4]. Changes in land use potentially affect the change impacts and the anthropogenic pressure on available water resources too (e.g. increased intercepted groundwater resources in the river Mirna catchment that precipitation in case of enlarging the forest area [5]). are used for drinking water supply in Northern Istria Water resource and supply vulnerability and risk (Croatia, Northern part of the Adriatic sea region) to give assessments, water scarcity estimates and drought analyses the basis for preparation of adaptation and mitigation due to climate change impacts are necessary for avoiding strategies up to year 2050. Analysing the impacts of future water crises and preparing adaptation measures to climate change on water resource availability consists of mitigate the consequences of such crises [6,7]. using RCMs to simulate the change in temperature and Numerous studies have investigated the impact of precipitation up to 2050. Then, based on the results from climate change on water resources worldwide (e.g. [8]); climate modelling, a hydrological model is applied to many have also analysed the impacts of human activities calculate the future average annual water resource on water resources (e.g. [9]). Recently, more research has availability and characteristic renewable water resources been conducted to simulate the impacts of climate change availability (critical period), which are compared to past on water resources in future. This can be done by using availability to estimate the changes. various methodologies [10]: coupling Global Circulation Water demand analysis was conducted for the present Models (GCMs) with hydrologic models through demand and for five future water demand scenarios. To downscaling techniques, coupling high-resolution estimate the water resource vulnerability in Northern Istria, Regional Climate Models (RCMs) with hydrologic models the Water Exploitation Index (WEI) was calculated [20]. and using hypothetical scenarios as inputs to hydrologic However, to encompass the strong seasonal variability of models. Coupling high-resolution RCMs with hydrologic the water demand and water resource availability, a models has frequently been used to model the climate modified Characteristic Water Exploitation Index (CWEI) change impacts on hydrological regimes and water was also used. resources in the mid- to long-term future in Europe [11, The 2012 drought, which was more extreme than any 12]. considered future scenario, was also examined.

366 Technical Gazette 25, Suppl. 2(2018), 366-374 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia)

2 STUDY AREA The area of the Mirna catchment is most significant in terms of the available groundwater and surface water The river Mirna catchment is the largest drainage basin resources included in the water supply system of Istarski and watercourse in the Istria peninsula and covers vodovod (Water Utility of Istria), the largest of the three approximately 700 km2 (Fig. 1). water supply companies in . Using spring water for water supply adds pressure to the water resources and the ecosystem of the Mirna River, particularly during the extremely dry years that are becoming increasingly more frequent. The coastal area that is supplied by these springs mostly host tourist activity, leading to increased water demand in the summer months, when the spring yield is the lowest. Severe dry events during the last several decades (e.g., 1986-89, 2002-03, and 2011-12) have shown that the exploitable water resources available in Istria within the constructed water supply systems are at the limit of meeting the current needs. A potential solution is to better optimise the provision of seasonal water reserves from the Butoniga reservoir (45°19'57.8" N 13°55'25.3" E), which also lies in the Mirna catchment (Fig. 1). This reservoir has a volume of approximately 20 million m3, 8 million m3 of

Figure 1 Mirna River catchment and location of springs Sv. Ivan, Bulaž and water is used for water supply annually. Gradole and Butoniga reservoir Due to the proximity of the individual spring catchments and the close occurrences of both wet and dry The area of Istrian Peninsula is spreading over 3476 2 2 periods, the water balance characteristics of these three km , of which 2820 km administratively belongs to Istria most significant spring water intakes in this area (i.e., Sv. County. The Mirna catchment area belongs to the Ivan, Gradole and Bulaž) are presented and analysed in the periphery of the Adriatic Carbonate platform. This aggregate in this paper (Fig. 2). geological structure includes carbonate and clastic deposits with stratigraphic ranges from the Upper Jurassic to the Eocene. The parts of the Istrian Peninsula where the surface watercourses are developed are mostly composed of flysch. The northern and northeastern parts of Istria are characterized by significant structural disturbances of the high carbonate massif of Mt Učka and Mt Ćićarija. The central and southeastern parts of Istria belong to the Pazin flysch basin, while the northwestern edge of this area belongs to the Trieste flysch basin. The Buje carbonate anticline rises between these basins, while the western and southwestern parts belong to the western Istrian carbonate anticline. The Mirna River formed its course between the abovementioned structures and partly through a valley area composed of an alluvial deposit reaching deep below sea level, thus retarding groundwater flow. Groundwater emerges from the aquifer, in the form of several significant karst springs in the Mirna catchment at a contact point between the karst hinterland and the alluvial deposits. These springs are Sv. Ivan in the upper Mirna course (45°24'03.2" N 13°58'39.5" E), Bulaž in its middle course (45°22'46.5" N 13°53'17.4" E), and Gradole in its lower course (45°20'37.9" N 13°42'10.9" E) (Fig. 1). The already observed manifestations of climate change are predicted to intensify in this area, where the majority of Figure 2 Distribution of: a) the average monthly discharge and abstracted flow run-off goes underground, and karst springs are the main of Sv. Ivan, Gradole and Bulaž springs and Butoniga reservoir (2003-2014); b) water supply resource [21]. Inter-annual distribution of the total discharge and water pumping of Sv. Ivan, Approximately 50% of the Mirna water balance (11.3 Gradole and Bulaž springs and Butoniga reservoir (2003-2014) with the inter- annual distribution of the total discharge in the extremely dry 2011-2012 m3 s−1 estimated at the river mouth) is accounted for by the

Sv. Ivan (0.82 m3 s−1), Gradole (2.1 m3 s−1) and Bulaž (1.4 Data used for this research (overflow and abstracted m3 s−1) springs, as well as by several other minor springs water quantities at selected springs that were used for (e.g., Tombazin) that are not under the official hydrological estimation of springs yield) are provided by Croatian monitoring programme [22]. Meteorological and Hydrological Service based on their During prolonged dry periods, water flowing from the monitoring system. karst springs is almost the only inflow to the Mirna River.

Tehnički vjesnik 25, Suppl. 2(2018), 366-374 367 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia)

During dry summer periods, approximately 3.57 modelling of the annual runoff is based on the acceptable million tourists (as registered during 2015) are visiting − correlation (r = 0.85) between average annual and lowest dramatically increasing the permanent population of average monthly discharges of the analysed springs in the approximately 210.000. The increased water demand Mirna river basin. This correlation was determined from during summer is affected not only by tourist activities but the regression analysis of available historical data and also by the demand for water to irrigate private lawns and discharge measurements in the period of 1961-2013. community parks. Additionally, the generated data series of the lowest These springs are highly sensitive to climate change average monthly discharges were determined, which and droughts that can significantly reduce the available usually represent a critical factor in securing the water water balance of these springs. The year 2012 was availability during an increased seasonal water supply particularly critical as the area experienced a low water demands in the analysed area that is characterized by event with a return period of between 100 and 200 years strong tourism activities. [23]. Due to the high uncertainty in estimation of future climate characteristics three climate models were used. The 3 METHODOLOGY discharge data were generated by regional climate models 3.1 Methodology for Analysing the Impact of Climate REGCM3 [30], ALADIN [31] and PROMES [32]. The Change on Water Resources selected RCMs were forced by the observed and predicted concentrations of the greenhouse gases (GHGs) based on The methodology used to assess the impact of climate several scenarios, including the IPCC’s change on water resources in the analysed area of Northern (Intergovernmental Panel on Climate Change) A1B Istria was described in detail by Rubinić and Katalinić [24]. scenario of the GHGs emissions for the period after 2001. The proposed model uses a runoff estimation based on The initial and boundary data for each RCM were provided a spatial distribution of the annual rainfall and air from different global climate models (GCMs): the temperature in the GIS environment. The localized ECHAM5 GCM data were used to force REGCM3, measurements at specific points are distributed over the ALADIN was forced by the Arpege GCM and PROMES entire basin area using point-weighted averages. The was forced by the HadCM3Q GCM [33]. Langbein [25] and Turc [26] empirical expressions were A homogeneity assessment of the results based on the used for this purpose. The choice of an appropriate runoff historical time series and on the two chosen models was distribution was based on a comparison of data from basins performed using the Wilcoxon test [34]. The trend analysis with available observations of climatological indicators was conducted, both in terms of a common approach based and measured discharges. The Turc method was used for on linear correlation and also by using the Theil-Sen's regional hydrological water balance assessment for karst estimator [35, 36]. Testing the significance of trends was basins [27], but in this case study the Langbein method was carried out using nonparametric Man-Kendall's test [37, chosen as the most appropriate for the analysed karstic 38]. springs located in the Mirna river catchment [28]. This concurs with an established practice in regional 3.2 Methodology for Estimation of the Water Exploitation hydrological approach of using empirical models that are Index calibrated based on the results of hydrological observations during the period of 1961-2013 [27-29]. The Water Exploitation Index (WEI) was applied to The approach used here is based on the analysis of the estimate the water resource vulnerability. WEI is a ratio of historical climatological and hydrological data (1961- the average annual total water demand to the average 2013) to generate the data for the period of 2014-2050. annual available water resources and is often used to assess Using these models along with the spatial assessment of the water stress at a national level based on total water use and annual rainfall and the average annual air temperatures in the average annual water availability [20]. However, such the analysed basin and determining the basin surface area an analysis cannot fully reflect the stress at a local level, using hydro-geological methods, it is possible to define the e.g., river basins or systems of karst springs. Furthermore, spatial distribution of the actual annual rainfall, i.e., the because the original WEI is based on mean annual data, it rainfall that infiltrated into the karst aquifer basin. does not account for seasonal variations in water demand In the process of modelling, both point and spatially or availability. Seasonal variations are especially important distributed data for the annual rainfall and the average in coastal Mediterranean regions, such as Northern Istria, annual air temperatures were used. Pazin, the main where the domestic, tourist and agricultural water demand climatological station located in the central part of the peak coincides with minimum water resources availability Istrian Peninsula, was selected as the reference station, and in summer. Considering these specific concerns, the the historically recorded data from the period of 1961-2013 original formula was modified here for local analysis and were analysed. The spatial distributions of the average critical periods. annual air temperature and precipitation for the reference Water Exploitation Index (WEI) was computed to time period of 1961-1990 were also used. Estimations of assess the average annual conditions as a ratio of the the average annual air temperature and precipitation for the Average Water Demand (WD) to the Average Water time period of 2014-2050 were based on the available data Resources (WR): from the main climatological station. Then, the impacts of climate change on hydrological WEI = WD/WR (1) characteristics, the average annual discharge and the lowest average monthly discharges, were estimated. The

368 Technical Gazette 25, Suppl. 2(2018), 366-374 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia)

The Characteristic Water Exploitation Index (CWEI) 4 RESULTS AND DISCUSSION was used to assess the vulnerability of water resources 4.1 Impact of Climate Change on Water Resources considering the strong seasonal variability in Northern Istria. In particular, the characteristic water demand Results of the generated minimum average monthly focused on August, which is a typical summer month discharge according to the three climatological models and characterized by very high temperatures and low their future estimates based on the historically available precipitation along with increased tourism and agricultural aggregate average monthly discharge from the springs Sv. water needs. CWEI is defined as the ratio of the Ivan, Gradole and Bulaž for the period of 1961-1990 are Characteristic Water Demand (CWD) to the Characteristic presented in Fig. 3. Water Resources (CWR):

CWEI = CWD/CWR (2)

Water demands and resources in Northern Istria were assessed using a simplified approach based on the statistical analysis of the observed hydrological data (i.e., abstracted and total flow) from Sv. Ivan, Gradole and Bulaž springs as well as the Butoniga reservoir. Average Water Demand (WD) was computed as the long-term mean annual abstracted flow, whereas Characteristic Water Demand (CWD) was computed as the long-term mean August abstracted flow, from Sv. Ivan, Gradole and Bulaž springs, and the Butoniga reservoir. Water resources were based mainly on the measured total flow from the Sv. Ivan, Gradole and Bulaž springs. The main issue was accounting for the water reserves in the Butoniga reservoir. Clearly, omitting these quantities from the resource analysis would overestimate the WEI and CWEI. However, the Butoniga reservoir does not have any external inflow other than direct precipitation. Therefore, two water resources scenarios were evaluated: scenario 1 was used to estimate water resources by considering total flows only at the Sv. Ivan, Gradole and Bulaž springs (WR1 and CWR1), and scenario 2 considered total flows at the springs and the Figure 3 Historical time series and projected time series of the total lowest abstracted flow from the Butoniga reservoir (WR2 and average monthly discharge of Sv. Ivan, Gradole and Bulaž springs generated CWR2). The average water resources (WR1 and WR2) were using different climate models for 1961-2050 with accompanying trends: A) computed as the mean annual total flow, whereas the REGCM3, B) ALADIN, and C) PROMES models characteristic water resources (CWR1 and CWR2) were The trends show that on a longer timescale and 2050, a computed as the minimum mean monthly total flow. decreasing trend in the selected characteristic discharge is In addition to the long-term statistical data, the expected to continue. More importantly, considering the extremely dry year of 2012 was examined in more detail to water availability of the analysed springs, the trends determine how these results match long-term projections. suggest a possibility for a more frequent occurrence of the Both the average Water Exploitation Index WEI2012 (2012 extremely low values of the lowest average monthly calendar year and hydrological year) and the Characteristic discharges. Water Exploitation Index CWEI2012 (the critical month of However, each of the applied models gives different August 2012) were considered. scenarios for the future changes and different slopes of For the original method [39], WEI < 0.1 indicates no these trends. According to the implemented Mann-Kendal stress, while WEI > 0.4 indicates severe stress. Although test, the trend for the entire analysed series of historical this classification is reasonable for average conditions at a data and projected values for the future (up to 2050), at the national level, when considering characteristic water significance level of 5%, there is no apparent decrease of conditions at a local level, these thresholds are too mean annual flow rates according to results obtained by the rigorous. Both Alcamo et al. [40] and Smakhtin et al. [41] use of REGCM3 (P-value 0.216) and the ALADIN model recognized that these threshold values are too low, and they (P-value 0.101), while in the results using PROMES, such defined slightly higher boundaries. This work used a a trend (P-value 0.031) was established. This statistically similar classification that was proposed in a CC-WaterS significant trend (Fig. 3) for the discharges generated by project that considered climate change and its impacts on the PROMES model amounts to 0.45 m3 s−1 over 100 years. water supply in South-eastern Europe: WEI < 0.50 In other words, the PROMES model predicts a decrease indicates low risk, 0.5 ≤ WEI < 0.7 indicates possible of the lowest average monthly discharges for almost a third difficulties, 0.7 ≤ WEI < 1.0 indicates strong risk, and WEI of the measured historical data. ≥ 1.0 is considered to be unsustainable [33]. The homogeneity of the historical and generated time

series of inflows based on REGCM3, ALADIN and

PROMES models results was analysed using the Wilcoxon

Tehnički vjesnik 25, Suppl. 2(2018), 366-374 369 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia) test. According to the results of this test, analysed series of historical period of 1960-2013 and the entire projected historical (for the 30-year reference series 1961-1990, as period of 2014-2050. well as in the case of a more complete historical series from The average values of the minimum average monthly 1961 to 2013) and generated future data (30-year series discharge from the end of the generated period (2021- 2021-2050, or in the case of a more complete sequence 2050) are significantly lower than the corresponding values analysis of 2014-2050), are mutually homogeneous in all from the 30-year historical period (1961-1990) in the analysed cases. inflow series for the entire climate models used. For the This analysis shows also that the lowest non- discharge generated using the REGCM3 model, this homogeneity was recorded for the REGCM3 model. This difference is the smallest with a discharge decrease of model is usually used in the wider region of the analysed 8.6%, while for the discharge generated using the Croatian localities and it has been used for the longest for PROMES model, this difference is the largest with a climate predictions caused by climate change [42]. The decrease of 15.6%. However, more prominent differences results of these models were used as input values in are expected regarding an increase of the discharge hydrological models, with which hydrological changes in variability, as well as a more frequent occurrence of the the water regime of water resources were generated in lower average monthly discharges, generated by the other areas of Croatia [27, 33]. ALADIN model (66.9%). Similar results are found when Tab. 1 presents the relationship between the projected the data generated by the selected climate models for the lowest average monthly discharge for the future periods period 1914-2050 are compared to the historical data from and the historical inflows, which were determined using 1961-2013. This is also true when the generated data in a measured historical data, as well as the generated data characteristic 30-year period (2021-2050) is compared to based on measured annual rainfall and temperatures. the historical data from 1961-1990. Possible differences in The comparison also analysed the relationship the occurrence of the minimal values generated by all three between two characteristic 30-year periods, i.e., the climate models are even more pronounced and amount up reference historical period of 1961- 1990 and the projected to 80%. period of 2021-2050, as well as the entire available

Table 1 Statistical analysis of the measured and generated aggregate lowest average monthly discharge from Sv. Ivan, Gradole and Bulaž springs, expressed as a percentage relative to the historical series, 1961-1990 and 1961-2013, (Note: Avg - average, SD - standard deviation, Cv - coefficient of variation, Max - maximum, and Min - minimum) 3 −1 3 −1 3 −1 3 −1 Avg (m s ) SD (m s ) Cv Max (m s ) Min (m s ) Measured historical discharges 1961-1990 1,60 0,65 0,41 2,88 0,70 1961-2013 1,41 0,64 0,45 3,28 0,57 Historical discharges generated from the measured precipitation and temperatures 1961-2013 1,42 1,07 0,75 5,06 0,18 Historical discharges generated by the climate models (1961.-2013.) REGCM3 1,42 0,72 0,51 3,14 0,27 ALADIN 1,42 0,69 0,49 3,81 0,38 PROMES 1,41 0,71 0,50 3,75 0,41 Comparison of the future discharges generated by the climate models and the measured historical discharges 2021-2050/1961-1990 (%) (%) (%) (%) (%) REGCM3 −8,6 −8,2 0,43 −11,3 −35,4 ALADIN −11,6 23,5 39,8 9,6 −82,1 PROMES −15,6 4,6 23,9 4,1 −57,4 2014-2050/1961-2013 (%) (%) (%) (%) (%) REGCM3 2,5 −8,3 −10,5 −22,0 −21,5 ALADIN 2,5 29,8 26,7 −3,6 −78,3 PROMES −0,62 17,2 17,9 8,9 −48,3 Comparison of the historical and future discharges generated by the climate models 2021-2050/1961-1990 (%) (%) (%) (%) (%) REGCM3 2,6 −19,0 −21,1 −18,7 64,7 ALADIN −2,8 5,8 8,9 −17,1 −66,9 PROMES −9,0 −12,7 −4,0 −19,9 −42,8 2014-2050/1961-2013 (%) (%) (%) (%) (%) REGCM3 2,3 −18,9 −20,7 −18,7 64,7 ALADIN 2,1 19,2 16,7 −17,1 −66,9 PROMES −0,7 4,5 5,2 −4,8 −28,3

However, a decrease of the average discharges is found according to the REGCM3 model, they could decrease by only in the data series generated by the ALADIN model 11.3%. In addition, the variability of the analysed lowest (−9%), and only for the period closer to the middle of the average monthly discharge is expected to increase. 21st century. If the generated and historical data of the lowest When the generated data for the future period of 2014- average monthly discharge after 2014 and until the end of 2050 are compared to the historical data from the period of 2013 are compared, smaller discharge differences and 1961-2013, the analysed maximum values of the lowest variabilities are obtained. The reason for this could be the average monthly discharge show different results: change of dynamics, i.e., the gradually increasing impacts according to the PROMES and ALADIN models, they of climate change on discharge, or because climate change could even increase by 4.1% and 9.6%, respectively, while has already somewhat manifested in the historical and

370 Technical Gazette 25, Suppl. 2(2018), 366-374 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia) generated periods that were not covered by the selected 30- population in the Istria County increased from 206 344 in year reference period (1991-2020). 2001 to 208 055 in 2011, which amounts to 0.08% per year. This increase is largely attributed to the immigration from 4.2 Water Exploitation Index other parts of the country and is not expected to rise in the future [43, 44]. Considering a linear continuation of this The results of the hydrological analyses were used to trend, the population by 2050 is estimated to reach 215.000 assess the potential impacts of climate change, i.e., a (a 3.2% increase). The accommodation capacities, on the general decrease in discharge based on the exploitation of other hand, are expected to increase from 210 000, which water for water supply needs. For this purpose, the Water were available in 2001, to 285.000 by 2050 [42], which Exploitation Index was calculated for Northern Istria, amounts to a 35.7% increase. Therefore, if these ambitious considering average (annual) and characteristic (monthly) plans are realised, the population and accommodation hydrological conditions. In addition to the current water capacities will together reach 500.000 by the year 2050, resources (1991-2014), past values (1961-1990) and and the total water demand is estimated to increase up to several future predictions (2021-2050) from the three 25%. It should be stressed that a decrease of the water climate models (i.e., REGCM3, ALADIN and PROMES) demand could also be feasible if a different approach to were considered. Similarly, in addition to the current water water demand management issued (i.e. green demand (1991-2014), several future (2021-2050) scenarios infrastructure, grey water reuse, artificial aquifer recharge, were considered with varying increases in the current water better management of the water supply losses, an increased demand of up to 25% with increments of 5%. These water supply efficiency in general, etc.) but this is not increases were estimated from the long-term population analysed in this paper. projections and planned accommodation capacities for Tab. 2 shows the estimated WEI and CWEI for tourists. According to the Croatian census [43], the total Northern Istria.

Table 2 WEI and CWEI for Northern Istria 3 −1 WR1 (WR2) (m s ) Average annual Past Present Future 2021-2050 conditions 1961-1990 1991-2014 REGCM3 ALADIN PROMES 4.8 (4.897) 4.299 (4.396) 4.64 (4.737) 4.5 (4.597) 4.83 (4.927) 3 −1 WD (m s ) WEI1 = WD/WR1 (WEI2 = WD/WR2) 1991-2014 0.71 0.15 (0.15) 0.16 (0.16) 0.15 (0.15) 0.16 (0.16) 0.14 (0.14) Future 5% 0.73 0.15 (0.15) 0.17 (0.17) 0.16 (0.15) 0.16 (0.16) 0.15 (0.15) Future 10% 0.77 0.16 (0.16) 0.18 (0.17) 0.17 (0.16) 0.17 (0.17) 0.16 (0.16) Future 15% 0.80 0.17 (0.16) 0.19 (0.18) 0.17 (0.17) 0.18 (0.17) 0.17 (0.16) Future 20% 0.84 0.17 (0.17) 0.19 (0.19) 0.18 (0.18) 0.19 (0.18) 0.17 (0.17) Future 25% 0.87 0.18 (0.18) 0.20 (0.20) 0.19 (0.18) 0.19 (0.19) 0.18 (0.18) 3 −1 CWR1 (CWR2) (m s ) Characteristic monthly Past Present Future 2021-2050 conditions 1961-1990 1991-2014 REGCM3 ALADIN PROMES 1.6 (1.809) 1.176 (1.385) 1.46 (1.669) 1.41 (1.619) 1.35 (1.559) 3 −1 CWD (m s ) CWEI1 = CWD/CWR1 (CWEI2 = CWD/CWR2) 1991-2014 1.13 0.71 (0.63) 0.96 (0.82) 0.78 (0.68) 0.80 (0.70) 0.84 (0.73) Future 5% 1.19 0.74 (0.66) 1.01 (0.86) 0.82 (0.71) 0.84 (0.74) 0.88 (0.76) Future 10% 1.25 0.78 (0.69) 1.06 (0.90) 0.85 (0.75) 0.88 (0.77) 0.92 (0.80) Future 15% 1.30 0.82 (0.72) 1.11 (0.94) 0.89 (0.78) 0.92 (0.81) 0.97 (0.84) Future 20% 1.36 0.85 (0.75) 1.16 (0.98) 0.93 (0.82) 0.97 (0.84) 1.01 (0.87) Future 25% 1.42 0.89 (0.78) 1.21 (1.02) 0.97 (0.85) 1.01 (0.88) 1.05 (0.91)

Average Water Demand (WD) was calculated as the WEI values are similar and suggest a very low risk even if mean annual abstracted flow from the Sv. Ivan, Gradole the future water demand increases by 25%. and Bulaž springs and the Butoniga reservoir in the period When the original [39] boundary values are considered, of 1991-2014 (with future increases of 5-25%). Average all the WEI values indicate moderate water stress. For past Water Resources were calculated as the mean annual total water resources, CWEI1 indicates a strong risk for all water flow at the Sv. Ivan, Gradole and Bulaž springs (WR1), and demand scenarios. When present water resources are as the sum of WR1 and the mean annual abstracted flow considered, CWEI1 indicates a strong current risk and an from Butoniga reservoir (WR2), in the past (1961-1990), overexploitation of the karst springs for all future demands. present (1991-2014), and future (2021-2050), as predicted For future water resources, all climate models predict by three climate models: REGCM3, ALADIN and higher CWEI1 values than the past ones, suggesting a PROMES. Characteristic Water Demand (CWD) was strong risk for most future water demand scenarios and computed from the mean August abstracted flow from the overexploitation for increases in water demand over 20% Sv. Ivan, Gradole and Bulaž springs as well as the Butoniga or 25%, depending on the climate model. The results for reservoir; whereas, Characteristic Water Resources were present water resources that indicate even stronger risks computed as the minimum mean monthly flow observed at than any future scenario are somewhat misleading, because all three springs (CWR1), and as the sum of CWR1 and the the present scenario includes an extremely dry event that mean August abstracted flow from the Butoniga reservoir occurred in August 2012. Future modelled scenarios, (CWR2) for the past, present and future scenarios. When clearly, do not anticipate an occurrence of such a strong evaluating WEI using the CC-WaterS [33] thresholds, the drought in the period 2021-2050.

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2012 2012 To separately evaluate this extremely dry event from (WR2 ). Characteristic Water Demand (CWD ) was 2012, when a first-degree water restriction was declared in calculated as the mean August 2012 abstracted flow from the Istria County, and the karst springs were exploited to the three springs and the Butoniga reservoir, whereas the their maximum capacity, the WEI2012 for the calendar and Characteristic Water Resources (CWR2012) were calculated hydrological year and the CWEI2012 for August were as the mean August 2012 total flow at the three springs 2012 2012 additionally evaluated. (WR1 ) or the sum of WR1 and the abstracted flow 2012 2012 Water Demand (WD ) was calculated as the mean from the Butoniga reservoir (WR2 ). 2012 abstracted flow from the Sv. Ivan, Gradole and Bulaž From the results presented in Tab. 3, the hydrological springs and the Butoniga reservoir, whereas the water year (possible difficulties) was much more critical than the resources were calculated as the mean 2012 total flow at calendar year (low risk). 2012 2012 2012 the three springs (WR1 ), and the sum of the WR1 and Furthermore, CWEI1 > 1.0 for August indicates the 2012 abstracted flow from the Butoniga reservoir overexploitation and an unsustainable situation.

Table 3 WEI for the extremely dry year of 2012 in Northern Istria 2012 3 −1 2012 2012 3 −1 2012 2012 Period WD (m s ) WR1 (WR2 ) (m s ) WEI1 (WEI2 ) January 2012 - December 2012 0.71 2.20 (2.35) 0.32 (0.30) October 2011 - September 2012 0.72 1.28 (1.45) 0.57 (0.50) 2012 3 −1 2012 2012 3 −1 2012 2012 3 −1 Period CWD (m s ) CWR1 (CWR2 ) (m s ) CWEI1 (CWEI2 ) (m s ) August 2012 1.01 0.59 (1.01) 1.71 (1.00)

This event is clearly characterized by a much longer suggesting a strong risk for most future water demand return period than any future scenario considered here. scenarios and overexploitation for increases in water Nevertheless, such events are not isolated and could be demand greater than 20%. expected again in the future. The extreme dry event that occurred in the summer of 2012 was also examined; the WEI for 2012 and the CWEI 5 CONCLUSIONS for August 2012 were also calculated. The results clearly show that the hydrological year (possible difficulties) was This paper shows that the analysed Northern Istria much more critical than the calendar year (low risk). region, i.e., the Sv. Ivan, Gradole, and Bulaž springs in Furthermore, the CWEI for August indicates Mirna river catchment, has risks of unwanted overexploitation and an unsustainable situation that consequences of climate change and that until the year resulted in a first-degree water restriction that was declared 2050, even more extreme changes can be expected. in the Istria County in 2012 when the karst springs were Different models for forecasting changes in climate exploited to their maximum capacity. This event was more indicators result in different scenarios of the impact of such extreme than any estimated future scenario. Nevertheless, changes on the selected water balance indicators. Even the such events are not isolated and could be expected again in most conservative REGCM3 climate model projected that the future. It can also be concluded that using water from the lowest monthly discharge in the analysed springs the Butoniga reservoir in addition to the water from Sv. during the period of 2021-2050 could be approximately Ivan, Gradole and Bulaž springs to meet the water demand 8.6% lower than the average of the 30-year period of 2021- during critical periods lowers the CWEI by as much as 2050 and that the extreme minimums could be up to 35.4% 19%. lower with far more extreme variations and a potential for Sustainable water resource management requires even drier years than the extremely dry 2011-12 season. optimization of the use and also the reduction of excessive The projections of the other two models used in this paper, exploitation of available water resources. Therefore, to ALADIN and PROMES, suggest even more pronounced ensure the required water supply quantities and the differences and significantly lower average and extremely functionality of the water supply system in Istria in the low values of the lowest average monthly discharge. All given climate scenarios and their hydrological the trends show a decrease in the analysed discharge and consequences, it is essential to develop adequate scenarios therefore the water resources available for water supply. of management and structural responses for the spatial and The WEI results for Northern Istria for average temporal allocation of available resources in cases that are conditions (the mean annual abstracted flow from the Sv. far more unfavourable than the current scenario. Ivan, Gradole and Bulaž springs, with and without the The methodology presented in this paper can be applied Butoniga reservoir), using the CC-WaterS [33] thresholds, to other water resources and locations where the seasonal indicate that there is a very low risk of not meeting future character in water resources availability and water demand water demands even if they increase by 25%. Similarly, is present. It can be used for longer periods estimation (e.g. when the original [39] boundary values are considered, all until 2100) which gives the possibility to decision makers of the values indicate moderate water stress. to better prepare adequate management and structural Considering the seasonal variability in Northern Istria, responses. the CWEI for past water availability indicates a strong risk for all water demand scenarios. For the current water Acknowledgements resources, CWEI indicates a strong current risk; however, any future increases in water demand would result in This research was supported by the EU IPA Adriatic overexploitation of the karst springs if the Butoniga Cross-Border Cooperation Programme 2007-2013, under reservoir is not included. The predicted CWEIs for future project 1°STR./0004, DRINKADRIA: Networking for water resources are also higher than the past ones, Drinking Water Supply in the Adriatic Region; and the

372 Technical Gazette 25, Suppl. 2(2018), 366-374 Barbara KARLEUŠA et al.: Analysis of Climate Change Impact on Water Supply in Northern Istria (Croatia)

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